> I'd skip this for now - it does not allow any kind of interactive conversation - as I learned after downloading 5G of models - it's a proof of concept that takes a wav file in.
I haven't looked into it that much but to my understanding a) You just need an audio buffer and b) Thye seem to support streaming (or at least it's planed)
> Looking at the library’s trajectory — ASR, streaming TTS, multilingual synthesis, and now speech-to-speech — the clear direction was always streaming voice processing. With this release, PersonaPlex supports it.
> You just need an audio buffer
That alone to do right on macOS using Swift is an exercise in pain that even coding bots aren't able to solve first time right :)
I beg to differ. My agent just one-shotted a MicrophoneBufferManager in swift when asked.
Complete with AVFoundation and a tap for the audio buffer.
It really is trivial.
Any chance of pushing it to GitHub? My swift knowledge could be written out on an oversized beer coaster currently, so I'm still collecting useful snippets
https://gist.github.com/gabereiser/cd8c67262717afd2539dc9c3d...
I've also had great results with using LLMs to pry into Apple's private and undocumented APIs. I've been impressed with the lack of hallucinations for C/C++ and Obj-C functions.
I can attest that the quality in this domain has greatly improved over the years too. I am not always fan of the quality of the Swift code that my LLM produces, but I am impressed that what is often produced works in one shot, as well. The quality also is not that important to me because I can just refactor the logic myself, and often prefer to do it anyway. I cannot hold an LLM to any idiosyncrasies that I do not share with it.
Exactly. Even if it’s a skeleton, as long as it does “The Thing”, I’m happy. I can always refactor into something useful.